Analysis of the algorithm: From kernels to backup genes.

Kernelization section

The algorithm transformed the semantic similarity matrix to make it compatible with a kernel. Once this was done for each network and kernel type, it was integrated by kernel type. Below there is a general analysis of the properties of each matrix in the different phases of the process.

Matrix properties

Table 1. Similarity matrixes

Net Matrix_Dimensions Matrix_Elements Matrix_Elements_Non_Zero
small_pro 200x200 40000 40000
small_pro_two 200x200 40000 40000

Table 2. Uncombined kernel matrixes

Net Kernel Matrix_Dimensions Matrix_Elements Matrix_Elements_Non_Zero
small_pro rf 200x200 40000 40000
small_pro_two rf 200x200 40000 40000
small_pro ct 200x200 40000 40000
small_pro_two ct 200x200 40000 40000

Table 3. Integrated kernel matrixes

Integration Kernel Matrix_Dimensions Matrix_Elements Matrix_Elements_Non_Zero
mean rf 200x200 40000 40000
mean ct 200x200 40000 40000

Weight values